Data checked 2026-08-13. Data may be stale - beyond the review cycle.
Review cycles are documented on the Methodology page. Methodology
TixiaoShan/LIO-SAM
Algorithm Tier A slam_vio BSD-3-Clause
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Engineering Snapshot
Use cases & tasks 5
- Best suited for
-
- Autonomous ground/air vehicles requiring 3D LiDAR-inertial SLAM
- Engineers integrating Velodyne or Ouster LiDARs with IMU for state estimation
- Primary tasks
-
- 3D mapping and localization
- Autonomous navigation in structured/unstructured environments
- Robot pose estimation with LiDAR-IMU fusion
Stack & ecosystem
- Resource type
- Algorithm
- Ecosystem
- 3d-mapping · lidar-inertial · lidar-odometry · lidar-slam · loam-velodyne · ouster
License & compliance
- License
-
BSD-3-Clause(Inferred)
Lifecycle & freshness Show
- Maintenance
- Active
- Latest version
- Not recorded
- Last activity
- 2026-08-13
- Last checked
- 2026-08-13
- Verification
- Official confirmed
What It Solves
Provides tightly-coupled LiDAR-inertial odometry and mapping via factor graph smoothing for 3D localization and mapping in GPS-denied environments.
Primary use cases
- 3D mapping and localization
- Autonomous navigation in structured/unstructured environments
- Robot pose estimation with LiDAR-IMU fusion
Secondary use cases
- Surveying and inspection missions
- Multi-session mapping with loop closure
When to Use
Consider when
- ROS 1 (Melodic/Noetic) environment is available
- LiDAR is Velodyne or Ouster (per repo topics)
- Factor graph optimization (GTSAM) fits compute budget
- Tightly-coupled LiDAR-IMU fusion is required over loosely-coupled
Verify before adopting
- ROS version compatibility with target platform
- LiDAR model and firmware compatibility (Velodyne/Ouster)
- Real-time performance on target compute (CPU/GPU)
- IMU noise characteristics and calibration procedure
- Loop closure reliability in target environment
Start Here
Adoption Checklist
- Needs verification ROS version compatibility with target platform
- Needs verification LiDAR model and firmware compatibility (Velodyne/Ouster)
- Needs verification Real-time performance on target compute (CPU/GPU)
- Needs verification IMU noise characteristics and calibration procedure
- Needs verification Loop closure reliability in target environment
Each check stays "needs verification" until an official source confirms it; unconfirmed items are never marked verified.
Known Limitations & Unknowns
Known limitations
- Supplied facts do not specify ROS 2 support
- Supplied facts do not specify compute requirements or real-time guarantees
- Supplied facts do not detail loop closure implementation
Not publicly verified
- Minimum IMU rate and noise specs
- Supported LiDAR firmware versions
- Map size scalability
- Multi-robot / collaborative mapping support
Alternatives & Related Tools
Alternatives
- fast-lio — Alternative to
How is it used?
Start from the recorded entry points below, then validate against the technical checklist.
- Official site https://github.com/TixiaoShan/LIO-SAM
- Repository https://github.com/TixiaoShan/LIO-SAM
- Documentation https://github.com/TixiaoShan/LIO-SAM
Technical checklist
- OK License identified Recorded: BSD-3-Clause
- OK Maintenance signal Active
- OK Verification status Official confirmed
- OK Source evidence attached 1 source record(s)
- NEEDS REVIEW Latest version recorded Not recorded
Official Links
Metadata & Governance
| License | BSD-3-Clause — Inferred |
|---|---|
| Commercial model | Unknown |
| Maintenance status | Active |
| Verification status | Official confirmed — Confirmed via the official repository API responses in SourceRefs below. |
| Latest version | Not recorded |
| Latest release | Not recorded |
| Last activity | 2026-08-13 |
| Last checked | 2026-08-13 |
| First seen | Not recorded |
Dataset facts
Facts above come from the official dataset card only; unconfirmed fields stay unknown.
Related Resources & Dependencies
- fast-lio — alternative to (verified)
Recent Activity
New resource: TixiaoShan/LIO-SAM
New repository resource added by the sprint promote pipeline.
Related Knowledge
Guides
- Evaluating SLAM / VIO Systems for UAV Use — A repeatable checklist for comparing open-source SLAM and visual-inertial odometry systems before integrating them into a UAV stack.
Collections
- SLAM / VIO Stack Evaluation — Open-source localization and mapping systems for UAV navigation, inspection and mapping missions.